Contextual Prediction for Handheld Device Interaction

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Solution Overview

Problem

Handheld computing devices face challenges in providing rapid, accurate, and natural user interfaces due to the absence of full-size keyboards and mice, leading to increased delay and error in interaction.

Innovation Solution

A method that automatically detects environmental cues and user actions, learns relevant cue combinations, and predicts user actions or configures the device accordingly to anticipate and streamline user interactions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Volume of moving object

If reduced-key keyboards or touch-sensitive panels are used to make portable computers smaller, then the device size is reduced, but the user interface interaction becomes slower and more error-prone

Engineering Contradiction:

Improvedevice sizeVSAvoidinteraction speed

Core Design Contradiction:

Volume of moving objectVSProductivity

Solution Approach 1:

The system performs preliminary actions by detecting environmental cues and learning user behavior patterns in advance, then proactively presents predicted inputs or actions before the user actually needs them. This anticipatory approach compensates for the slower interaction speed of reduced-key keyboards by pre-positioning likely inputs, thereby maintaining device compactness while improving interaction efficiency

Inventive Principle:

Principle #10Preliminary action

2Volume of moving object

If reduced-key keyboards or touch-sensitive panels are used to make portable computers smaller, then the device size is reduced, but the error rate in user interaction increases

Engineering Contradiction:

Improvedevice sizeVSAvoidinteraction accuracy

Core Design Contradiction:

Volume of moving objectVSReliability

Solution Approach 1:

The system continuously monitors user interactions and environmental cues, then uses this feedback to refine its predictions of user intent. By comparing predicted inputs with actual user actions, the system learns from errors and improves accuracy over time, thereby maintaining small device size while reducing interaction errors through adaptive learning

Inventive Principle:

Principle #23Feedback

3Productivity

If contextual prediction is implemented to improve interaction speed, then the system complexity increases

Engineering Contradiction:

Improveinteraction speedVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system performs self-service by automatically detecting environmental cues, learning user behavior patterns, and generating predictions without requiring complex external processing or intervention. The device uses its own sensors, processors, and stored data to autonomously improve interaction speed, thereby achieving faster performance while limiting the need for additional complex external systems

Inventive Principle:

Principle #25Self-service

Data Source

PatentEP2013761B1Contextual prediction of user words and user actions

Publication Date: 2016.11.02 TEGIC COMM INC

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AI summary

An operating sequence for a handheld computing device manages the device to automatically detect cues describing the device's environmental and user actions performed with the device, learn which cues and cue combinations are relevant to predict user actions, and then in response to occurrence of the relevant cues, predictively implementing the appropriate user action or configuring the device in anticipation of user action.